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Stochastic Pattern of Health Care Spending: Evidence from Nonlinear Panel Data Analysis

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dc.contributor.author Yasar, Nermin
dc.date.accessioned 2024-04-25T07:32:34Z
dc.date.available 2024-04-25T07:32:34Z
dc.date.issued 2021
dc.identifier.citation Yasar, N. (2021). "Stochastic Pattern of Health Care Spending: Evidence from Nonlinear Panel Data Analysis", Review of Economics and Finance, Vol.19, pp.264-270. tr_TR
dc.identifier.issn 19237529
dc.identifier.uri http://hdl.handle.net/20.500.12416/7932
dc.description.abstract This paper analyses the stochastic pattern of health care spending for 188 countries around the world which are categorized into four groups based on the World Bank income categories. The main motivation of this ar-ticle is to evaluate whether the stochastic features of total health care expenditure varies if decomposed into private and public health care consumption. To achieve this goal, in addition to conventional empirical methods, latterly de-veloped panel stationarity approaches are employed for both linear and nonlinear regression processes. Our results demonstrate that allowing for cross-section dependency between series and nonlinearity in the estimation process may lead to more often rejection of the null hypothesis of unit root for all series in panel data set. tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof 10.55365/1923.X2021.19.27 tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject Health Care Consumption tr_TR
dc.subject Heterogeneous Panel Unit Root tr_TR
dc.subject Nonlinearity tr_TR
dc.subject Panel Cross Section Dependence tr_TR
dc.subject Panel Unit Root Test tr_TR
dc.title Stochastic Pattern of Health Care Spending: Evidence from Nonlinear Panel Data Analysis tr_TR
dc.type article tr_TR
dc.relation.journal Review of Economics and Finance tr_TR
dc.contributor.authorID 230528 tr_TR
dc.identifier.volume 19 tr_TR
dc.identifier.startpage 264 tr_TR
dc.identifier.endpage 270 tr_TR
dc.contributor.department Çankaya Üniversitesi, Meslek Yüksek Okulu, Dış Ticaret Bölümü tr_TR


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